Author Archives: Frank Stelter

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Pulse arrival time (PAT) and pulse transit time (PTT) derived from the finger have been widely investigated for noninvasive blood pressure (BP) measurement. The study investigates the feasibility of BP measurement using a chest-worn patch sensor derived systolic timing intervals and pulse timing measurements. Healthy volunteers (N=14, 38 ± 13 years) carried out a protocol including deep breathing test, sustained hand grip test and modified Valsalva test with continuous physiological measurements from a patch sensor attached on left chest and intermittent BP measurements from an automated oscillometric monitor as a reference. The efficacy of chest derived PAT and PTT for univariate BP prediction is assessed using correlation and regression slope. The cross validation performance of predicting BP using multivariate regression model with chest derived systolic timing intervals and pulse timing features were also evaluated. The results suggest that the chest derived PAT and PTT had modest correlations (-0.52 and -0.31) and regression slopes (-0.21 and -0.14) with automated oscillometric systolic and diastolic BP references, respectively. On the other hand, a multivariate regression approach for prediction of mean blood pressure (MBP) using patch sensor measurements showed a correlation of 0.72, mean error of 0.1 mmHg and RMSE error of 5.1 mmHg compared to the oscillometric MBP values. The study demonstrated the feasibility of BP measurement using a wearable chest-worn patch sensor in healthy control subjects.

Feasibility of Noninvasive Blood Pressure Measurement using a Chest-worn Patch Sensor

Pulse arrival time (PAT) and pulse transit time (PTT) derived from the finger have been widely investigated for noninvasive blood pressure (BP) measurement. The study investigates the feasibility of BP measurement using a chest-worn patch sensor derived systolic timing intervals and pulse timing measurements. Healthy volunteers (N=14, 38 ± 13 years) carried out a protocol including deep breathing test, sustained hand grip test and modified Valsalva test with continuous physiological measurements from a patch sensor attached on left chest and intermittent BP measurements from an automated oscillometric monitor as a reference. The efficacy of chest derived PAT and PTT for univariate BP prediction is assessed using correlation and regression slope. The cross validation performance of predicting BP using multivariate regression model with chest derived systolic timing intervals and pulse timing features were also evaluated. The results suggest that the chest derived PAT and PTT had modest correlations (-0.52 and -0.31) and regression slopes (-0.21 and -0.14) with automated oscillometric systolic and diastolic BP references, respectively. On the other hand, a multivariate regression approach for prediction of mean blood pressure (MBP) using patch sensor measurements showed a correlation of 0.72, mean error of 0.1 mmHg and RMSE error of 5.1 mmHg compared to the oscillometric MBP values. The study demonstrated the feasibility of BP measurement using a wearable chest-worn patch sensor in healthy control subjects.

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Sleep is a renowned marker of health. One in three adults endure sleep disorders without diagnosis due to lack of effective sleep screening technology. The study presents clinical validation of VitalPatch®, a wireless adhesive medical device for screening of sleep architecture in normal and apnea compared to the Polysomnography (PSG).

Performance of adhesive patch for screening of sleep architecture

Sleep is a renowned marker of health. One in three adults endure sleep disorders without diagnosis due to lack of effective sleep screening technology. The study presents clinical validation of VitalPatch®, a wireless adhesive medical device for screening of sleep architecture in normal and apnea compared to the Polysomnography (PSG).

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Tremendous interest prevails in developing a convenient and effective wearable medical device for evaluating sleep at home. The current study presents the clinical validation of VitalPatch®, a wireless adhesive patch sensor for screening of sleep architecture compared to the gold standard polysomnograph (PSG). A group of 45 volunteers were attached to a standard 22-channel PSG and a VitalPatch sensor on their chest. Simultaneous PSG and patch data were acquired overnight wirelessly. Hypnograms with wake, non-rapid eye movement (NREM), and REM stages were obtained using both the methods for a sequence of 30 s epochs corresponding to the bed-time, and the respective statistical sleep metrics were computed in 42 subjects. Performance, statistical and agreement analyses were conducted using VitalPatch’s sleep assessments compared to the PSG. The accuracy and Cohen’s kappa measures of 3-class sleep stage prediction (n=42) was 80.5±8.3% and 0.50±0.18, respectively. Total sleep time showed a strong linear correlation (r=0.88) with a mean absolute error (MAE) of 25 min compared to the PSG. NREM and REM sleep times were highly correlated to the PSG (r=0.82 and r=0.71, respectively) with MAE of 26 min and 16 min, respectively. The results suggest that unobtrusive disposable VitalPatch sensor is effective in predicting sleep architectures highly comparable to the PSG and can be useful for widespread screening of sleep patterns in home environment.

Screening of Sleep Architecture using a Disposable Patch Sensor

Tremendous interest prevails in developing a convenient and effective wearable medical device for evaluating sleep at home. The current study presents the clinical validation of VitalPatch®, a wireless adhesive patch sensor for screening of sleep architecture compared to the gold standard polysomnograph (PSG). A group of 45 volunteers were attached to a standard 22-channel PSG and a VitalPatch sensor on their chest. Simultaneous PSG and patch data were acquired overnight wirelessly. Hypnograms with wake, non-rapid eye movement (NREM), and REM stages were obtained using both the methods for a sequence of 30 s epochs corresponding to the bed-time, and the respective statistical sleep metrics were computed in 42 subjects. Performance, statistical and agreement analyses were conducted using VitalPatch’s sleep assessments compared to the PSG. The accuracy and Cohen’s kappa measures of 3-class sleep stage prediction (n=42) was 80.5±8.3% and 0.50±0.18, respectively. Total sleep time showed a strong linear correlation (r=0.88) with a mean absolute error (MAE) of 25 min compared to the PSG. NREM and REM sleep times were highly correlated to the PSG (r=0.82 and r=0.71, respectively) with MAE of 26 min and 16 min, respectively. The results suggest that unobtrusive disposable VitalPatch sensor is effective in predicting sleep architectures highly comparable to the PSG and can be useful for widespread screening of sleep patterns in home environment.

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Development of wearable medical devices to measure noninvasive blood pressure (NIBP) has recently been evolving at finger/wrist and earlobe locations. The study investigates the predictive power of pulse transit time (PTT) and pulse arrival time (PAT) measured at finger and earlobe sites for BP measurement during two unique physiological interventions: handgrip test (HGT) and modified Valsalva test (mVT). Singlelead electrocardiogram, impedance cardiogram, infrared photoplethysmogram (PPG) from finger and earlobe, and CNAP® NIBP were simultaneously acquired in 14 healthy subjects (39±11 years); beat-to-beat BP, PAT and PTT were extracted; linear regression, correlation and statistical analyses were carried out. The results show that both the BP interventions caused significant increase (P<0.05) in diastolic blood pressure (DBP), but concurrent significant decrease (P<0.01) in PTT was observed only during mVT in both finger and earlobe sites. On the other hand, PAT did not change significantly during both the BP interventions. PTT showed highest correlation (R2) of 0.47±0.26 and negative regression slope of −0.39±0.31 with DBP in finger during mVT compared to earlobe. Thus, the predictive power of PTT for NIBP monitoring vary broadly in distinct BP regulation mechanisms, and found to be moderate in finger site and relatively weak in earlobe site.

Assessment of Pulse Transit/Arrival Time as Noninvasive Blood Pressure Predictors in Finger and Earlobe Sites

Development of wearable medical devices to measure noninvasive blood pressure (NIBP) has recently been evolving at finger/wrist and earlobe locations. The study investigates the predictive power of pulse transit time (PTT) and pulse arrival time (PAT) measured at finger and earlobe sites for BP measurement during two unique physiological interventions: handgrip test (HGT) and modified Valsalva test (mVT). Singlelead electrocardiogram, impedance cardiogram, infrared photoplethysmogram (PPG) from finger and earlobe, and CNAP® NIBP were simultaneously acquired in 14 healthy subjects (39±11 years); beat-to-beat BP, PAT and PTT were extracted; linear regression, correlation and statistical analyses were carried out. The results show that both the BP interventions caused significant increase (P<0.05) in diastolic blood pressure (DBP), but concurrent significant decrease (P<0.01) in PTT was observed only during mVT in both finger and earlobe sites. On the other hand, PAT did not change significantly during both the BP interventions. PTT showed highest correlation (R2) of 0.47±0.26 and negative regression slope of −0.39±0.31 with DBP in finger during mVT compared to earlobe. Thus, the predictive power of PTT for NIBP monitoring vary broadly in distinct BP regulation mechanisms, and found to be moderate in finger site and relatively weak in earlobe site.